Sensors

Research

26 pages, 1919 KiB

Open AccessArticle

Cascade Sliding Mode Control for Linear Displacement Positioning of a Quadrotor

by Albert Sawiński, Piotr Chudzik and Karol Tatar

Sensors 2025, 25(3), 883; https://doi.org/10.3390/s25030883 (registering DOI) - 31 Jan 2025

Viewed by 297

This paper contains an example of a simulation implementation of sliding mode control algorithms for the problem of adjusting the linear position of a quadrotor. A mathematical model of the drone was proposed, which was then implemented in a simulation environment. The method [...] Read more.

This paper contains an example of a simulation implementation of sliding mode control algorithms for the problem of adjusting the linear position of a quadrotor. A mathematical model of the drone was proposed, which was then implemented in a simulation environment. The method of designing sliding mode controllers using the Lyapunov method in order to improve stability was presented. A cascade system based entirely on sliding mode control algorithms is introduced. The article ends with a comparative analysis of simulation test results of classical control systems and controllers based on sliding mode control. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

21 pages, 6330 KiB

Open AccessArticle

Variable-Parameter Impedance Control of Manipulator Based on RBFNN and Gradient Descent

by Linshen Li, Fan Wang, Huilin Tang and Yanbing Liang

Sensors 2025, 25(1), 49; https://doi.org/10.3390/s25010049 - 25 Dec 2024

Viewed by 445

Abstract

During the interaction process of a manipulator executing a grasping task, to ensure no damage to the object, accurate force and position control of the manipulator’s end-effector must be concurrently implemented. To address the computationally intensive nature of current hybrid force/position control methods, [...] Read more.

During the interaction process of a manipulator executing a grasping task, to ensure no damage to the object, accurate force and position control of the manipulator’s end-effector must be concurrently implemented. To address the computationally intensive nature of current hybrid force/position control methods, a variable-parameter impedance control method for manipulators, utilizing a gradient descent method and Radial Basis Function Neural Network (RBFNN), is proposed. This method employs a position-based impedance control structure that integrates iterative learning control principles with a gradient descent method to dynamically adjust impedance parameters. Firstly, a sliding mode controller is designed for position control to mitigate uncertainties, including friction and unknown perturbations within the manipulator system. Secondly, the RBFNN, known for its nonlinear fitting capabilities, is employed to identify the system throughout the iterative process. Lastly, a gradient descent method adjusts the impedance parameters iteratively. Through simulation and experimentation, the efficacy of the proposed method in achieving precise force and position control is confirmed. Compared to traditional impedance control, manual adjustment of impedance parameters is unnecessary, and the method can adapt to tasks involving objects of varying stiffness, highlighting its superiority. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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12 pages, 354 KiB

Open AccessArticle

Green ILC: A Novel Energy-Efficient Iterative Learning Control Approach

by Yu Dou and Emmanuel Prempain

Sensors 2024, 24(23), 7787; https://doi.org/10.3390/s24237787 - 5 Dec 2024

Viewed by 576

Abstract

In this paper, we introduce Green Iterative Learning Control (Green ILC), an innovative hybrid control method that addresses the critical need for energy-efficient control in dynamic, repetitive-task environments. By integrating the iterative refinement capabilities of traditional Iterative Learning Control (ILC) with the optimization [...] Read more.

In this paper, we introduce Green Iterative Learning Control (Green ILC), an innovative hybrid control method that addresses the critical need for energy-efficient control in dynamic, repetitive-task environments. By integrating the iterative refinement capabilities of traditional Iterative Learning Control (ILC) with the optimization strengths of gradient descent, Green ILC achieves a balanced trade-off between tracking accuracy and energy consumption. This novel approach introduces a cost function that minimizes both tracking errors and control effort, enabling the system to adaptively optimize performance over iterations. Theoretical analysis and simulation results demonstrate that Green ILC not only achieves faster convergence but also provides significant energy savings compared with traditional ILC methods. Notably, Green ILC reduces energy consumption by prioritizing efficiency, making it particularly suitable for energy-intensive applications such as robotics, manufacturing, and process control. While a slight decrease in tracking accuracy is observed, this trade-off is acceptable for scenarios where energy efficiency is paramount. This work establishes Green ILC as a promising solution for modern industrial systems requiring robust and sustainable control strategies. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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16 pages, 4634 KiB

Open AccessArticle

A Real-Time Semantic Map Production System for Indoor Robot Navigation

by Raghad Alqobali, Reem Alnasser, Asrar Rashidi, Maha Alshmrani and Tareq Alhmiedat

Sensors 2024, 24(20), 6691; https://doi.org/10.3390/s24206691 - 17 Oct 2024

Viewed by 1173

Abstract

Although grid maps help mobile robots navigate in indoor environments, some lack semantic information that would allow the robot to perform advanced autonomous tasks. In this paper, a semantic map production system is proposed to facilitate indoor mobile robot navigation tasks. The developed [...] Read more.

Although grid maps help mobile robots navigate in indoor environments, some lack semantic information that would allow the robot to perform advanced autonomous tasks. In this paper, a semantic map production system is proposed to facilitate indoor mobile robot navigation tasks. The developed system is based on the employment of LiDAR technology and a vision-based system to obtain a semantic map with rich information, and it has been validated using the robot operating system (ROS) and you only look once (YOLO) v3 object detection model in simulation experiments conducted in indoor environments, adopting low-cost, -size, and -memory computers for increased accessibility. The obtained results are efficient in terms of object recognition accuracy, object localization error, and semantic map production precision, with an average map construction accuracy of 78.86%. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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22 pages, 8684 KiB

Open AccessArticle

U-TAG: Electromagnetic Wireless Sensing System for Robotic Hand Pre-Grasping

by Armin Gharibi, Filippo Costa and Simone Genovesi

Sensors 2024, 24(16), 5340; https://doi.org/10.3390/s24165340 - 18 Aug 2024

Viewed by 869

Abstract

In order to perform complex manipulation and grasp tasks, robotic hands require sensors that can handle increasingly demanding functionality and degrees of freedom. This research paper proposes a radiofrequency sensor that uses a wireless connection between a probe and a tag. A compact [...] Read more.

In order to perform complex manipulation and grasp tasks, robotic hands require sensors that can handle increasingly demanding functionality and degrees of freedom. This research paper proposes a radiofrequency sensor that uses a wireless connection between a probe and a tag. A compact and low-profile antenna is mounted on the hand and functions as a probe to read a printed passive resonator on the plastic object being targeted, operating within a pre-touch sensing range. The grasping strategy consists of four stages that involve planar alignment in up-to-down and left-to-right directions between the probe and tag, the search for an appropriate distance from the object, and rotational (angular) alignment. The real and imaginary components of the probe-input impedance are analyzed for different orientation strategies and positioning between the resonator on the object and the probe. These data are used to deduce the orientation of the hand relative to the target object and to determine the optimal position for grasping. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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13 pages, 3540 KiB

Open AccessArticle

Liquid-Driven Microinjection System for Precise Fundus Injection

by Shiyu Xu, Bo Hu, Rongxin Liu, Xin Zhao and Mingzhu Sun

Sensors 2024, 24(7), 2140; https://doi.org/10.3390/s24072140 - 27 Mar 2024

Viewed by 1224

Abstract

Microinjection is usually applied to the treatment of some retinal disorders, such as retinal vein cannulation and displaced submacular hemorrhage. Currently, the microinjection procedure is usually performed by using the viscous fluid control of a standard vitrectomy system, which applies a fixed air [...] Read more.

Microinjection is usually applied to the treatment of some retinal disorders, such as retinal vein cannulation and displaced submacular hemorrhage. Currently, the microinjection procedure is usually performed by using the viscous fluid control of a standard vitrectomy system, which applies a fixed air pressure through foot pedal activation. The injection process with the fixed pressure is uncontrollable and lacks feedback, the high flow rate of the injected drug may cause damage to the fundus tissue. In this paper, a liquid-driven microinjection system with a flow sensor is designed and developed specifically for fundus injection. In addition, a PID sliding mode control (SMC) method is proposed to achieve precise injection in the injection system. The experimental results of fundus simulation injection demonstrate that the microinjection system meets the requirements of fundus injection and reduces the impact of the injection process on the fundus tissue. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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17 pages, 5144 KiB

Open AccessArticle

Trampoline Stiffness Estimation by Using Robotic System for Quantitative Evaluation of Jumping Exercises

by Gunseok Park, Seung-Hwan Choi, Chang-Hyun Kim, Min Young Kim and Suwoong Lee

Sensors 2023, 23(24), 9645; https://doi.org/10.3390/s23249645 - 6 Dec 2023

Viewed by 2176

Abstract

Trampolines are recognized as a valuable tool in exercise and rehabilitation due to their unique properties like elasticity, rebound force, low-impact exercise, and enhancement of posture, balance, and cardiopulmonary function. To quantitatively assess the effects of trampoline exercises, it is essential to estimate [...] Read more.

Trampolines are recognized as a valuable tool in exercise and rehabilitation due to their unique properties like elasticity, rebound force, low-impact exercise, and enhancement of posture, balance, and cardiopulmonary function. To quantitatively assess the effects of trampoline exercises, it is essential to estimate factors such as stiffness, elements influencing jump dynamics, and user safety. Previous studies assessing trampoline characteristics had limitations in performing repetitive experiments at various locations on the trampoline. Therefore, this research introduces a robotic system equipped with foot-shaped jigs to evaluate trampoline stiffness and quantitatively measure exercise effects. This system, through automated, repetitive movements at various locations on the trampoline, accurately measures the elastic coefficient and vertical forces. The robot maneuvers based on the coordinates of the trampoline, as determined by its torque and position sensors. The force sensor measures data related to the force exerted, along with the vertical force data at X, Y, and Z coordinates. The model’s accuracy was evaluated using linear regression based on Hooke’s Law, with Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient Squared (R-squared) metrics. In the analysis including only the distance between X and the foot-shaped jigs, the average MAE, RMSE, and R-squared values were 17.9702, 21.7226, and 0.9840, respectively. Notably, expanding the model to include distances in X, Y, and between the foot-shaped jigs resulted in a decrease in MAE to 15.7347, RMSE to 18.8226, and an increase in R-squared to 0.9854. The integrated model, including distances in X, Y, and between the foot-shaped jigs, showed improved predictive capability with lower MAE and RMSE and higher R-squared, indicating its effectiveness in more accurately predicting trampoline dynamics, vital in fitness and rehabilitation fields. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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17 pages, 1591 KiB

Open AccessArticle

Cautious Bayesian Optimization: A Line Tracker Case Study

by Vicent Girbés-Juan, Joaquín Moll, Antonio Sala and Leopoldo Armesto

Sensors 2023, 23(16), 7266; https://doi.org/10.3390/s23167266 - 18 Aug 2023

Cited by 1 | Viewed by 1395

Abstract

In this paper, a procedure for experimental optimization under safety constraints, to be denoted as constraint-aware Bayesian Optimization, is presented. The basic ingredients are a performance objective function and a constraint function; both of them will be modeled as Gaussian processes. We incorporate [...] Read more.

In this paper, a procedure for experimental optimization under safety constraints, to be denoted as constraint-aware Bayesian Optimization, is presented. The basic ingredients are a performance objective function and a constraint function; both of them will be modeled as Gaussian processes. We incorporate a prior model (transfer learning) used for the mean of the Gaussian processes, a semi-parametric Kernel, and acquisition function optimization under chance-constrained requirements. In this way, experimental fine-tuning of a performance objective under experiment-model mismatch can be safely carried out. The methodology is illustrated in a case study on a line-follower application in a CoppeliaSim environment. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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13 pages, 5459 KiB

Open AccessCommunication

Obstacle Detection in Infrared Navigation for Blind People and Mobile Robots

by Ioannis Papagianopoulos, Gilbert De Mey, Andrzej Kos, Boguslaw Wiecek and Vasilis Chatziathasiou

Sensors 2023, 23(16), 7198; https://doi.org/10.3390/s23167198 - 16 Aug 2023

Cited by 3 | Viewed by 2216

Abstract

The paper is a continuation of the authors’ work intended for infrared navigation for blind people and mobile robots. This concerns the detection of obstacles in the person’s or mobile robot’s trajectory, in particular, the detection of corners. The temperature distribution of a [...] Read more.

The paper is a continuation of the authors’ work intended for infrared navigation for blind people and mobile robots. This concerns the detection of obstacles in the person’s or mobile robot’s trajectory, in particular, the detection of corners. The temperature distribution of a building’s internal wall near a corner has been investigated. Due to geometry, more heat will be transferred by conduction so that inside the building, the temperature on the wall will be decreasing towards a corner. The problem will be investigated theoretically and numerically, and the results are confirmed by experimental measurements. The purpose of this research is to help blind people by equipping them with a small infrared camera that warns them when they are approaching a corner inside a building. The same aim is addressed to mobile robots. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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30 pages, 9253 KiB

Open AccessArticle

Design of A Finite-Time Adaptive Controller for Image-Based Uncalibrated Visual Servo Systems with Uncertainties in Robot and Camera Models

by Zhuoqun Zhao, Jiang Wang and Hui Zhao

Sensors 2023, 23(16), 7133; https://doi.org/10.3390/s23167133 - 11 Aug 2023

Cited by 1 | Viewed by 1390

Abstract

Aiming at the time-varying uncertainties of robot and camera models in IBUVS (image-based uncalibrated visual servo) systems, a finite-time adaptive controller is proposed based on the depth-independent Jacobian matrix. Firstly, the adaptive law of depth parameters, kinematic parameters, and dynamic parameters is proposed [...] Read more.

Aiming at the time-varying uncertainties of robot and camera models in IBUVS (image-based uncalibrated visual servo) systems, a finite-time adaptive controller is proposed based on the depth-independent Jacobian matrix. Firstly, the adaptive law of depth parameters, kinematic parameters, and dynamic parameters is proposed for the uncertainty of a robot model and a camera model. Secondly, a finite-time adaptive controller is designed by using a nonlinear proportional differential plus a dynamic feedforward compensation structure. By applying a continuous non-smooth nonlinear function to the feedback error, the control quality of the closed-loop system is improved, and the desired trajectory of the image is tracked in finite time. Finally, using the Lyapunov stability theory and the finite-time stability theory, the global finite-time stability of the closed-loop system is proven. The experimental results show that the proposed controller can not only adapt to the changes in the EIH and ETH visual configurations but also adapt to the changes in the relative pose of feature points and the camera’s relative pose parameters. At the same time, the convergence rate near the equilibrium point is improved, and the controller has good dynamic stability. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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14 pages, 4968 KiB

Open AccessArticle

Design, Construction and Control of a Manipulator Driven by Pneumatic Artificial Muscles

by Željko Šitum, Srečko Herceg, Nenad Bolf and Željka Ujević Andrijić

Sensors 2023, 23(2), 776; https://doi.org/10.3390/s23020776 - 10 Jan 2023

Cited by 9 | Viewed by 3110

Abstract

This paper describes the design, construction and experimental testing of a single-joint manipulator arm actuated by pneumatic artificial muscles (PAMs) for the tasks of transporting and sorting work pieces. An antagonistic muscle pair is used in a rotational sense to produce a required [...] Read more.

This paper describes the design, construction and experimental testing of a single-joint manipulator arm actuated by pneumatic artificial muscles (PAMs) for the tasks of transporting and sorting work pieces. An antagonistic muscle pair is used in a rotational sense to produce a required torque on a pulley. The concept, operating principle and elementary properties of pneumatic muscle actuators are explained. Different conceptions of the system realizations are analyzed using the morphological-matrix conceptual design framework and top-rated solution was practically realized. A simplified, control-oriented mathematical model of the manipulator arm driven by PAMs and controlled with a proportional control valve is derived. The model is then used for a controller design process. Fluidic muscles have great potential for industrial applications and assembly automation to actuate new types of robots and manipulators. Their characteristics, such as compactness, high strength, high power-to-weight ratio, inherent safety and simplicity, are worthy features for advanced manipulation systems. The experiments were carried out on a practically realized manipulator actuated by a pair of muscle actuators set into an antagonistic configuration. The setup also includes an original solution for the subsystem to add work pieces in the working space of the manipulator. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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21 pages, 2091 KiB

Open AccessArticle

A Two-Step Method for Dynamic Parameter Identification of Indy7 Collaborative Robot Manipulator

by Meseret Tadese, Nabih Pico, Sungwon Seo and Hyungpil Moon

Sensors 2022, 22(24), 9708; https://doi.org/10.3390/s22249708 - 11 Dec 2022

Cited by 7 | Viewed by 2784

Abstract

Accurate dynamic model is critical for collaborative robots to achieve satisfactory performance in model-based control or other applications such as dynamic simulation and external torque estimation. Such dynamic models are frequently restricted to identifying important system parameters and compensating for nonlinear terms. Friction, [...] Read more.

Accurate dynamic model is critical for collaborative robots to achieve satisfactory performance in model-based control or other applications such as dynamic simulation and external torque estimation. Such dynamic models are frequently restricted to identifying important system parameters and compensating for nonlinear terms. Friction, as a primary nonlinear element in robotics, has a significant impact on model accuracy. In this paper, a reliable dynamic friction model, which incorporates the influence of temperature fluctuation on the robot joint friction, is utilized to increase the accuracy of identified dynamic parameters. First, robot joint friction is investigated. Extensive test series are performed in the full velocity operating range at temperatures ranging from 19 °C to 51 °C to investigate friction dependency on joint module temperature. Then, dynamic parameter identification is performed using an inverse dynamics identification model and weighted least squares regression constrained to the feasible space, guaranteeing the optimal solution. Using the identified friction model parameters, the friction torque is computed for measured robot joint velocity and temperature. Friction torque is subtracted from the measured torque, and a non-friction torque is used to identify dynamic parameters. Finally, the proposed notion is validated experimentally on the Indy7 collaborative robot manipulator, and the results show that the dynamic model with parameters identified using the proposed method outperforms the dynamic model with parameters identified using the conventional method in tracking measured torque, with a relative improvement of up to 70.37%. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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13 pages, 5895 KiB

Open AccessArticle

Development of a Multi-Layer Marking Toolkit for Layout-Printing Automation at Construction Sites

by Eun Soo Park, Hee Chang Seo and An Yong Lee

Sensors 2022, 22(13), 4822; https://doi.org/10.3390/s22134822 - 25 Jun 2022

Cited by 3 | Viewed by 2401

Abstract

In this study, the development of a multi-layer marking toolkit was investigated to improve construction quality and mitigate the problem of irregular designs in the layout-printing work performed at construction sites. The quality of conventional layout-printing work is dependent on the skill of [...] Read more.

In this study, the development of a multi-layer marking toolkit was investigated to improve construction quality and mitigate the problem of irregular designs in the layout-printing work performed at construction sites. The quality of conventional layout-printing work is dependent on the skill of the worker, and construction quality can suffer owing to inconsistencies in drawings resulting from human error. In this study, these problems were analyzed, and a construction-site-layout-marking toolkit apparatus and mechanical unit, with a structure that allowed for multi-layer installation for automated implementation at construction sites, were developed. The marking toolkit and mechanical unit with the multi-layer structure were developed in a modular form so that each module can operate independently. Furthermore, each module was developed in manual mode to improve the system by acquiring information on the movement of the marking toolkit and multi-layer structure. Additionally, data on the layout-printing method was developed by connecting the system via Ethernet and operating a wireless joystick. Finally, experiments were performed on a road surface covered with B4 paper and concrete panels to confirm the operational feasibility of the system, which was developed to operate manually. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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29 pages, 6518 KiB

Open AccessArticle

System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs

by Luis F. Recalde, Bryan S. Guevara, Christian P. Carvajal, Victor H. Andaluz, José Varela-Aldás and Daniel C. Gandolfo

Sensors 2022, 22(13), 4712; https://doi.org/10.3390/s22134712 - 22 Jun 2022

Cited by 11 | Viewed by 4657

Abstract

Accurate trajectory tracking is a critical property of unmanned aerial vehicles (UAVs) due to system nonlinearities, under-actuated properties and constraints. Specifically, the use of unmanned rotorcrafts with accuracy trajectory tracking controllers in dynamic environments has the potential to improve the fields of environment [...] Read more.

Accurate trajectory tracking is a critical property of unmanned aerial vehicles (UAVs) due to system nonlinearities, under-actuated properties and constraints. Specifically, the use of unmanned rotorcrafts with accuracy trajectory tracking controllers in dynamic environments has the potential to improve the fields of environment monitoring, safety, search and rescue, border surveillance, geology and mining, agriculture industry, and traffic control. Monitoring operations in dynamic environments produce significant complications with respect to accuracy and obstacles in the surrounding environment and, in many cases, it is difficult to perform even with state-of-the-art controllers. This work presents a nonlinear model predictive control (NMPC) with collision avoidance for hexacopters’ trajectory tracking in dynamic environments, as well as shows a comparative study between the accuracies of the Euler–Lagrange formulation and the dynamic mode decomposition (DMD) models in order to find the precise representation of the system dynamics. The proposed controller includes limits on the maneuverability velocities, system dynamics, obstacles and the tracking error in the optimization control problem (OCP). In order to show the good performance of this control proposal, computational simulations and real experiments were carried out using a six rotary-wind unmanned aerial vehicle (hexacopter—DJI MATRICE 600). The experimental results prove the good performance of the predictive scheme and its ability to regenerate the optimal control policy. Simulation results expand the proposed controller in simulating highly dynamic environments that showing the scalability of the controller. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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22 pages, 5672 KiB

Open AccessArticle

CFHBA-PID Algorithm: Dual-Loop PID Balancing Robot Attitude Control Algorithm Based on Complementary Factor and Honey Badger Algorithm

by Jianan Lin, Rongjia Zheng, Yirong Zhang, Jinkai Feng, Wei Li and Kaiqing Luo

Sensors 2022, 22(12), 4492; https://doi.org/10.3390/s22124492 - 14 Jun 2022

Cited by 15 | Viewed by 3047

Abstract

The PID control algorithm for balancing robot attitude control suffers from the problem of difficult parameter tuning. Previous studies have proposed using metaheuristic algorithms to tune the PID parameters. However, traditional metaheuristic algorithms are subject to the criticism of premature convergence and the [...] Read more.

The PID control algorithm for balancing robot attitude control suffers from the problem of difficult parameter tuning. Previous studies have proposed using metaheuristic algorithms to tune the PID parameters. However, traditional metaheuristic algorithms are subject to the criticism of premature convergence and the possibility of falling into local optimum solutions. Therefore, the present paper proposes a CFHBA-PID algorithm for balancing robot Dual-loop PID attitude control based on Honey Badger Algorithm (HBA) and CF-ITAE. On the one hand, HBA maintains a sufficiently large population diversity throughout the search process and employs a dynamic search strategy for balanced exploration and exploitation, effectively avoiding the problems of classical intelligent optimization algorithms and serving as a global search. On the other hand, a novel complementary factor (CF) is proposed to complement integrated time absolute error (ITAE) with the overshoot amount, resulting in a new rectification indicator CF-ITAE, which balances the overshoot amount and the response time during parameter tuning. Using balancing robot as the experimental object, HBA-PID is compared with AOA-PID, WOA-PID, and PSO-PID, and the results demonstrate that HBA-PID outperforms the other three algorithms in terms of overshoot amount, stabilization time, ITAE, and convergence speed, proving that the algorithm combining HBA with PID is better than the existing mainstream algorithms. The comparative experiments using CF prove that CFHBA-PID is able to effectively control the overshoot amount in attitude control. In conclusion, the CFHBA-PID algorithm has great control and significant results when applied to the balancing robot. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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24 pages, 9688 KiB

Open AccessArticle

Task-Oriented Evaluation of the Feasible Kinematic Directional Capabilities for Robot Machining

by Saša Stradovnik and Aleš Hace

Sensors 2022, 22(11), 4267; https://doi.org/10.3390/s22114267 - 3 Jun 2022

Cited by 7 | Viewed by 2684

Abstract

Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities prior [...] Read more.

Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities prior to task execution, for which we need efficient algorithms, especially in the case of flexible robot applications. To provide accurate and physically consistent information about the maximum kinematic capabilities while considering the requirements of the task, an approach called the Decomposed Twist Feasibility (DTF) method is proposed in this study. The evaluation of the maximum feasible end-effector velocity is based on the idea of decomposition into the linear and angular motion capabilities, considering a typical robot machining task with synchronous linear and angular motion. The proposed DTF method is presented by the well-known manipulability polytope concept. Unlike the existing methods that estimate the kinematic performance capabilities in arbitrarily weighted twist space, or separately in the translation and the rotation subspace, our approach offers an accurate and simple solution for the determination of the total kinematic performance capabilities, which is often highly required, especially in the case of robot machining tasks. The numerical results obtained in this study show the effectiveness of the proposed approach. Moreover, the proposed DTF method could represent suitable kinematic performance criteria for the optimal placement of predefined tasks within the robot workspace. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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19 pages, 3212 KiB

Open AccessArticle

Implementation of Omni-D Tele-Presence Robot Using Kalman Filter and Tricon Ultrasonic Sensors

by Hassan Tariq, Muhammad Rashid, Asfa Javed, Muhammad Aaqib Riaz, Mohammed Sinky and Muhammad Yousuf Irfan Zia

Sensors 2022, 22(10), 3948; https://doi.org/10.3390/s22103948 - 23 May 2022

Cited by 2 | Viewed by 2785

Abstract

The tele-presence robot is designed to set forth an economic solution to facilitate day-to-day normal activities in almost every field. There are several solutions to design tele-presence robots, e.g., Skype and team viewer, but it is pretty inappropriate to use Skype and extra [...] Read more.

The tele-presence robot is designed to set forth an economic solution to facilitate day-to-day normal activities in almost every field. There are several solutions to design tele-presence robots, e.g., Skype and team viewer, but it is pretty inappropriate to use Skype and extra hardware. Therefore, in this article, we have presented a robust implementation of the tele-presence robot. Our proposed omnidirectional tele-presence robot consists of (i) Tricon ultrasonic sensors, (ii) Kalman filter implementation and control, and (iii) integration of our developed WebRTC-based application with the omnidirectional tele-presence robot for video transmission. We present a new algorithm to encounter the sensor noise with the least number of sensors for the estimation of Kalman filter. We have simulated the complete model of robot in Simulink and Matlab for the tough paths and critical hurdles. The robot successfully prevents the collision and reaches the destination. The mean errors for the estimation of position and velocity are 5.77% and 2.04%. To achieve efficient and reliable video transmission, the quality factors such as resolution, encoding, average delay and throughput are resolved using the WebRTC along with the integration of the communication protocols. To protect the data transmission, we have implemented the SSL protocol and installed it on the server. We tested three different cases of video resolutions (i.e.,

320 \times 280

,

820 \times 460

and

900 \times 590

) for the performance evaluation of the video transmission. For the highest resolution, our TPR takes 3.5 ms for the encoding, and the average delay is 2.70 ms with 900 × 590 pixels. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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16 pages, 2043 KiB

Open AccessArticle

Deep Q-Learning in Robotics: Improvement of Accuracy and Repeatability

by Marius Sumanas, Algirdas Petronis, Vytautas Bucinskas, Andrius Dzedzickis, Darius Virzonis and Inga Morkvenaite-Vilkonciene

Sensors 2022, 22(10), 3911; https://doi.org/10.3390/s22103911 - 21 May 2022

Cited by 20 | Viewed by 5150

Abstract

Recent industrial robotics covers a broad part of the manufacturing spectrum and other human everyday life applications; the performance of these devices has become increasingly important. Positioning accuracy and repeatability, as well as operating speed, are essential in any industrial robotics application. Robot [...] Read more.

Recent industrial robotics covers a broad part of the manufacturing spectrum and other human everyday life applications; the performance of these devices has become increasingly important. Positioning accuracy and repeatability, as well as operating speed, are essential in any industrial robotics application. Robot positioning errors are complex due to the extensive combination of their sources and cannot be compensated for using conventional methods. Some robot positioning errors can be compensated for only using machine learning (ML) procedures. Reinforced machine learning increases the robot’s positioning accuracy and expands its implementation capabilities. The provided methodology presents an easy and focused approach for industrial in situ robot position adjustment in real-time during production setup or readjustment cases. The scientific value of this approach is a methodology using an ML procedure without huge external datasets for the procedure and extensive computing facilities. This paper presents a deep q-learning algorithm applied to improve the positioning accuracy of an articulated KUKA youBot robot during operation. A significant improvement of the positioning accuracy was achieved approximately after 260 iterations in the online mode and initial simulation of the ML procedure. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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17 pages, 3774 KiB

Open AccessArticle

Singular Configuration Analysis and Singularity Avoidance with Application in an Intelligent Robotic Manipulator

by Helin Wang, Ziqiang Zhou, Xianyou Zhong and Qijun Chen

Sensors 2022, 22(3), 1239; https://doi.org/10.3390/s22031239 - 6 Feb 2022

Cited by 6 | Viewed by 3908

Abstract

Recently, robotic sensor systems have gained more attention annually in complex system sense strategies. The robotic sensors sense the information from itself and the environment, and fuse information for the use of perception, decision, planning, and control. As an important supplement to traditional [...] Read more.

Recently, robotic sensor systems have gained more attention annually in complex system sense strategies. The robotic sensors sense the information from itself and the environment, and fuse information for the use of perception, decision, planning, and control. As an important supplement to traditional industrial robots, co-bots (short for co-working robots) play an increasingly vital role in helping small and medium-sized enterprises realize intelligent manufacturing. They have high flexibility and safety so that they can assist humans to complete highly repetitive and high-precision work. In order to maintain robot safe operation in the increasing complex working environment and human–computer intelligent interactive control, this paper is concerned with the problem of applicant accuracy analysis and singularity avoidance for co-bots. Based on the dynamic model with load and torque sensors, which is used to detect the external force at the end of the robot, this paper systematically analyzes the causes of singularity phenomenon in the robot motion control. The inverse solution is obtained by analytical method and numerical method, respectively. In order to ensure the smooth and safe operation in the whole workspace, it is necessary for a robot to avoid singularity. Singularity avoidance schemes are utilized for different control tasks, including point-to-point control and continuous path control. Corresponding simulation experiments are designed to verify the effectiveness of different evasion schemes, in which the advantages and disadvantages are compared and analyzed. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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14 pages, 3321 KiB

Open AccessArticle

Integration and Testing of a High-Torque Servo-Driven Joint and Its Electronic Controller with Application in a Prototype Upper Limb Exoskeleton

by Manuel Andrés Vélez-Guerrero, Mauro Callejas-Cuervo and Stefano Mazzoleni

Sensors 2021, 21(22), 7720; https://doi.org/10.3390/s21227720 - 20 Nov 2021

Cited by 5 | Viewed by 3233

Abstract

Mechatronic systems that allow motorized activation in robotic exoskeletons have evolved according to their specific applications and the characteristics of the actuation system, including parameters such as size, mechanical properties, efficiency, and power draw. Additionally, different control strategies and methods could be implemented [...] Read more.

Mechatronic systems that allow motorized activation in robotic exoskeletons have evolved according to their specific applications and the characteristics of the actuation system, including parameters such as size, mechanical properties, efficiency, and power draw. Additionally, different control strategies and methods could be implemented in various electronic devices to improve the performance and usability of these devices, which is desirable in any application. This paper proposes the integration and testing of a high-torque, servo-driven joint and its electronic controller, exposing its use in a robotic exoskeleton prototype as a case study. Following a brief background review, the development and implementation of the proposal are presented, allowing the control of the servo-driven joint in terms of torque, rotational velocity, and position through a straightforward, closed-loop control architecture. Additionally, the stability and performance of the servo-driven joint were assessed with and without load. In conclusion and based on the obtained results, the servo-driven joint and its control system demonstrate consistent performance under the proposed test protocol (max values: angular velocity 97 °/s, torque 33 Nm, positioning RMSE 1.46°), enabling this approach for use in various applications related to robotic exoskeletons, including human performance enhancement, rehabilitation, or support for daily living activities. Full article

(This article belongs to the Special Issue Robotic Systems and Automatic Control: Mathematical Models, Technologies, Applications and Challenges)

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